Use of infrared spectroscopy for diagnosis of traumatic arthritis in horses

Infrared Spectroscopy of Synovial Fluid Shows Accuracy as an Early Biomarker in an Equine Model of Traumatic Osteoarthritis

Osteoarthritis is a leading cause of lameness and joint disease in horses. A simple, economical, and accurate diagnostic test is required for routine screening for OA. This study aimed to evaluate infrared (IR)-based synovial fluid biomarker profiling to detect early changes associated with a traumatically induced model of equine carpal osteoarthritis (OA). Unilateral carpal OA was induced arthroscopically in 9 of 17 healthy thoroughbred fillies; the remainder served as Sham-operated controls. The median age of both groups was 2 years. Synovial fluid (SF) was obtained before surgical induction of OA (Day 0) and weekly until Day 63. IR absorbance spectra were acquired from dried SF films. Following spectral pre-processing, predictive models using random forests were used to differentiate OA, Sham, and Control samples. The accuracy for distinguishing between OA and any other joint group was 80%. The classification accuracy by sampling day was 87%. For paired classification tasks, the accuracies by joint were 75% for OA vs. OA Control and 70% for OA vs. Sham. The accuracy for separating horses by group (OA vs. Sham) was 68%. In conclusion, SF IR spectroscopy accurately discriminates traumatically induced OA joints from controls.

Utility of Plasma Protein Biomarkers and Mid-infrared Spectroscopy for Diagnosing Fracture-related Infections: A Pilot Study

OBJECTIVES

To compare a large panel of plasma protein inflammatory biomarkers and mid-infrared (MIR) spectral patterns in patients with confirmed fracture-related infections (FRIs) with those in controls without infection.

DESIGN

Prospective case-control study.

SETTING

Academic, Level 1 trauma center.

PATIENTS

Thirteen patients meeting confirmatory FRI criteria were matched to 13 controls based on age, time after surgery, and fracture region.

INTERVENTION

Plasma levels of 49 proteins were measured using enzyme-linked immunosorbent assay techniques. Fourier transform infrared spectroscopy of dried films was used to obtain MIR spectra of plasma samples.

MAIN OUTCOME MEASUREMENTS

The main outcome measurements included plasma protein levels and MIR spectra of samples.

RESULTS

Multivariate analysis-based predictive model developed using enzyme-linked immunosorbent assay-based biomarkers had sensitivity, specificity, and accuracy of 69.2% ± 0.0%, 99.9% ± 1.0%, and 84.5% ± 0.6%, respectively, with platelet-derived growth factor-AB/BB, C-reactive protein, and MIG selected as the minimum number of variables explaining group differences ( P < 0.05). Sensitivity, specificity, and accuracy of the predictive model based on MIR spectra were 69.9% ± 6.2%, 71.9% ± 5.9%, and 70.9% ± 4.8%, respectively, with 6 wavenumbers as explanatory variables ( P < 0.05).

CONCLUSIONS

This pilot study demonstrates the feasibility of using a select panel of plasma proteins and Fourier transform infrared spectroscopy to diagnose FRIs. Preliminary data suggest that the measurement of these select proteins and MIR spectra may be potential clinical tools to detect FRIs. Further investigation of these biomarkers in a larger cohort of patients is warranted.

LEVEL OF EVIDENCE

Diagnostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Attenuated total reflection Fourier transform infrared as a primary screening method for cancer in canine serum

Cancer is a major cause of death in dogs worldwide, and the incidence of cancer in dogs is increasing. The attenuated total reflection Fourier transform infrared spectroscopic (ATR-FTIR) technique is a powerful tool for the diagnosis of several diseases. This method enables samples to be examined directly without pre-preparation. In this study, we evaluated the diagnostic value of ATR-FTIR for the detection of cancer in dogs. Cancer-bearing dogs (n = 30) diagnosed by pathologists and clinically healthy dogs (n = 40) were enrolled in this study. Peripheral blood was collected for clinicopathological diagnosis. ATR-FTIR spectra were acquired, and principal component analysis was performed on the full wave number spectra (4,000–650 cm⁻¹). The leave-one-out cross validation technique and partial least squares regression analysis were used to predict normal and cancer spectra. Red blood cell counts, hemoglobin levels and white blood cell counts were significantly lower in cancer-bearing dogs than in clinically healthy dogs (p < 0.01, p < 0.01 and p = 0.03, respectively). ATR-FTIR spectra showed significant differences between the clinically healthy and cancer-bearing groups. This finding demonstrates that ATR-FTIR can be applied as a screening technique to distinguish between cancer-bearing dogs and healthy dogs.

Infrared spectroscopy of serum as a potential diagnostic screening approach for naturally occurring canine osteoarthritis associated with cranial cruciate ligament rupture

OBJECTIVE

To evaluate infrared (IR) spectroscopy of serum as a screening tool to differentiate dogs affected by naturally occurring osteoarthritis (OA) associated with cranial cruciate ligament rupture (CrCLR) and controls.

METHOD

104 adult dogs with CrCLR (affected group) and 50 adult control dogs were recruited for this prospective observational study. Serum samples were collected preoperatively from CrCLR dogs and from a subset of these dogs at 4-, and 12-week post-surgical intervention to stabilize the affected stifles. Serum was collected once from control dogs. Dry films were made from serum samples, and IR absorbance spectra acquired. Data preprocessing, principal component analysis and multivariate analysis of covariance were performed to separate samples from the two groups, and to evaluate temporal differences. Weighted logistic regression with L1 regularization method was used to develop a predictive model. Model performance based on an independent test set was evaluated.

RESULTS

Spectral data analysis revealed significant separation between the sera of CrCLR and control dogs (P < 0.0001), but not amongst different time points in the OA group. The sensitivity, specificity, AUC and accuracy of the test set were 84.62%, 96.15%, 93.20% and 92.31% respectively.

CONCLUSIONS

These findings confirm the potential of IR-spectroscopy of serum with chemometrics methods to differentiate controls from dogs with OA associated with CrCLR. This is the first step in development of an economic, and comparatively simple IR-based screening serum test for OA. Utility of this tool as a clinical screening and diagnostic test requires further investigation and validation.

Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy to diagnose osteoarthritis in equine serum

BACKGROUND

Reliable and validated biomarkers for osteoarthritis (OA) are currently lacking.

OBJECTIVES

To develop an accurate and minimally invasive method to assess OA-affected horses and provide potential spectral markers indicative of disease.

STUDY DESIGN

Observational, cross-sectional study.

METHODS

Our cohort consisted of 15 horses with OA and 48 without clinical signs of the disease, which were used as controls. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy was used to investigate serum samples (50 μL) collected from these horses. Spectral processing and multivariate analysis revealed differences and similarities, allowing for detection of spectral biomarkers that discriminated between the two cohorts. A supervised classification algorithm, namely principal component analysis coupled with quadratic discriminant analysis (PCA-QDA), was applied to evaluate the diagnostic accuracy.

RESULTS

Segregation between the two different cohorts, OA-affected and controls, was achieved with 100% sensitivity and specificity. The six most discriminatory peaks were attributed to proteins and lipids. Four of the spectral peaks were elevated in OA horses, which could be potentially due to an increase in lipids, protein expression levels and collagen, all of which have been previously reported in OA. Two peaks were found decreased and were tentatively assigned to the reduction of proteoglycan content that is observed during OA.

MAIN LIMITATIONS

The control group had a wide range of ages and breeds. Presymptomatic OA cases were not included. Therefore, it remains unknown whether this test could also be used as an early diagnostic tool.

CONCLUSIONS

This spectrochemical approach could provide an accurate and cost-effective blood test, facilitating point-of-care diagnosis of equine OA.

Biomarkers for equine joint injury and osteoarthritis

We report the results of a symposium aimed at identifying validated biomarkers that can be used to complement clinical observations for diagnosis and prognosis of joint injury leading to equine osteoarthritis (OA). Biomarkers might also predict pre-fracture change that could lead to catastrophic bone failure in equine athletes. The workshop was attended by leading scientists in the fields of equine and human musculoskeletal biomarkers to enable cross-disciplinary exchange and improve knowledge in both. Detailed proceedings with strategic planning was written, added to, edited and referenced to develop this manuscript. The most recent information from work in equine and human osteoarthritic biomarkers was accumulated, including the use of personalized healthcare to stratify OA phenotypes, transcriptome analysis of anterior cruciate ligament (ACL) and meniscal injuries in the human knee. The spectrum of "wet" biomarker assays that are antibody based that have achieved usefulness in both humans and horses, imaging biomarkers and the role they can play in equine and human OA was discussed. Prediction of musculoskeletal injury in the horse remains a challenge, and the potential usefulness of spectroscopy, metabolomics, proteomics, and development of biobanks to classify biomarkers in different stages of equine and human OA were reviewed. The participants concluded that new information and studies in equine musculoskeletal biomarkers have potential translational value for humans and vice versa. OA is equally important in humans and horses, and the welfare issues associated with catastrophic musculoskeletal injury in horses add further emphasis to the need for good validated biomarkers in the horse. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:823-831, 2018.

Use of Fourier-transform infrared spectroscopy to quantify immunoglobulin G concentrations in alpaca serum

Background

Rapid, economical, and quantitative assays for measurement of camelid serum immunoglobulin G (IgG) are limited. In camelids, failure of transfer of maternal immunoglobulins has a reported prevalence of up to 20.5%. An accurate method for quantifying serum IgG concentrations is required.

Objective

To develop an infrared spectroscopy‐based assay for measurement of alpaca serum IgG and compare its performance to the reference standard radial immunodiffusion (RID) assay.

Animals

One hundred and seventy‐five privately owned, healthy alpacas.

Methods

Eighty‐two serum samples were collected as convenience samples during routine herd visits whereas 93 samples were recruited from a separate study. Serum IgG concentrations were determined by RID assays and midinfrared spectra were collected for each sample. Fifty samples were set aside as the test set and the remaining 125 training samples were employed to build a calibration model using partial least squares (PLS) regression with Monte Carlo cross validation to determine the optimum number of PLS factors. The predictive performance of the calibration model was evaluated by the test set.

Results

Correlation coefficients for the IR‐based assay were 0.93 and 0.87, respectively, for the entire data set and test set. Sensitivity in the diagnosis of failure of transfer of passive immunity (FTPI) ([IgG] <1,000 mg/dL) was 71.4% and specificity was 100% for the IR‐based method (test set) as gauged relative to the RID reference method assay.

Conclusions and Clinical Importance

This study indicated that infrared spectroscopy, in combination with chemometrics, is an effective method for measurement of IgG in alpaca serum.

Toward point-of-care diagnostic metabolic fingerprinting: quantification of plasma creatinine by infrared spectroscopy of microfluidic-preprocessed samples

Infrared (IR) spectroscopy has previously been established as a means to accurately quantify several serum and urine metabolites, based upon spectroscopy of dry films. The same technique has also provided the basis to develop certain diagnostic tests, developed in the 'metabolomics' spirit. Here, we report on the further development of an integrated microfluidic-IR technology and technique, customized with the aim of dramatically extending the capabilities of IR spectroscopy in both analytical and diagnostic (metabolomic) applications. By exploiting the laminar fluid diffusion interface (LFDI), serum specimens are processed to yield product streams that are better suited for metabolic fingerprinting; metabolites are captured within the aqueous product stream, while proteins (which otherwise dominate the spectra of films dried from serum) are present in much reduced concentration. Spectroscopy of films dried from the aqueous stream then provides enhanced diagnostic and analytical sensitivity. The manuscript introduces an LFDI card design that is customized for integration with IR spectroscopy, and details the development of a quantitative assay for serum creatinine--based upon LFDI-processed serum samples--that is substantially more accurate (standard error of calibration, SEC = 43 micromol/L) than the corresponding assay based upon unprocessed serum specimens (SEC = 138 micromol/L). Preliminary results of diffusion modeling are reported, and the prospects for further optimization of the technique, guided by accurate modeling, are discussed.